Abstract: The Intraclass correlation coeffcient (ICC) is commonly used to estimate the similarity between quantitative measures obtained from different sources. To date, overdispersed data is traditionally transformed so that the linear mixed model based ICC can be estimated. Such an approach has been utilitarian due to the absence of the negative binomial form of the ICC. We will report on the expression of the negative binomial ICC from a generalized linear mixed model which similar to the poisson ICC includes fixed effects. Furthermore, the negative binomial ICC included the distribution parameter for the amount of overdispersion (r). Simulations using a wide variety of inputs and negative binomial distribution parameters showed better performance of the negative binomial ICC compared to the ICC based on LMM even when negative binomial data was logarithm, or square root transformed. A second comparison using highly overdispersed data that targeted a wider range of ICC values showed that the mean of estimated ICC closely approximated the true ICC. Finally we apply the negative binomial ICC to a real data example from a reliability study for an environmental sampling protocol.